function [bstResult, timeElapsed, resAIO] = LKAMKC_single_dataset(Ks, Y, tauset, lambdaset, nRepeat)
[nSmp, ~, nKernel] = size(Ks);
nCluster = length(unique(Y));
if ~exist('nRepeat', 'var')
    nRepeat = 1;
end

if ~exist('tauset', 'var')
    tauset = [0.1:0.1:1];
end
if ~exist('lambdaset', 'var')
    lambdaset = 2.^[-15:1:15];
end


numker = size(Ks,3);


gamma3 = ones(numker,1)/numker;
KC3 = sumKbeta(Ks,gamma3);

tic;
resAIO = zeros(length(tauset) * length(lambdaset), 3);


iPara = 1;
for it =1:length(tauset)
    %Calculate Neighborhood of each sample
    NSt = genarateNeighborhood(KC3,round(tauset(it)*nSmp));%% tau*num
    A0 = zeros(nSmp);
    for i =1:nSmp
        A0(NSt(:,i),NSt(:,i)) = A0(NSt(:,i),NSt(:,i))+1;
    end
    
    %%%%%%%%%%%%%%%%%%%
    HE0 = calHessian(Ks,NSt,1);
    
    for il =1:length(lambdaset)
        res_lkamkc  = [];
        
        for i3 = 1:nRepeat
            [label_lkamkc,w,objHistory] = LKAMKC(Ks, HE0, A0, nCluster, lambdaset(il));
            res_lkamkc = [res_lkamkc; ClusteringMeasure(Y, label_lkamkc)];%#ok<AGROW>
        end
        iPara
        mean(res_lkamkc, 1)
        resAIO(iPara,:) = mean(res_lkamkc, 1);
        iPara = iPara + 1;
    end
end
bstResult = max(resAIO,[], 1);
timeElapsed = toc;